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Looking into Crystal Balls: A Laboratory Experiment on Reputational Cheap Talk


  • Ottaviani, Marco
  • Meloso, Debrah
  • Nunnari, Salvatore


We experimentally study cheap talk by reporters motivated by their reputation for being well informed. Evaluators assess reputation by cross checking the report with the realized state of the world. We manipulate the key drivers of misreporting incentives: the uncertainty about the state of the world and the beliefs of evaluators about the strategy of reporters. Consistent with theory, reporters are more likely to report truthfully when there is more uncertainty and when evaluators conjecture that reporters always report truthfully. However, the experiment highlights two phenomena not predicted by standard theory. First, a large fraction of reports is truthful, even when this is not a best response. Second, evaluators have diculty learning reporters' strategies and overreact to message accuracy. We show that a learning model where accuracy is erroneously taken to represent truthfulness ts well evaluators' behavior. This judgement bias reduces reporters' incentives to misreport and improves information transmission.

Suggested Citation

  • Ottaviani, Marco & Meloso, Debrah & Nunnari, Salvatore, 2018. "Looking into Crystal Balls: A Laboratory Experiment on Reputational Cheap Talk," CEPR Discussion Papers 13231, C.E.P.R. Discussion Papers.
  • Handle: RePEc:cpr:ceprdp:13231

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    1. Irlenbusch, Bernd & Sliwka, Dirk, 2006. "Career concerns in a simple experimental labour market," European Economic Review, Elsevier, vol. 50(1), pages 147-170, January.
    2. Charles A. Holt & Lisa R. Anderson, 1996. "Classroom Games: Understanding Bayes' Rule," Journal of Economic Perspectives, American Economic Association, vol. 10(2), pages 179-187, Spring.
    3. Gilat Levy, 2007. "Decision Making in Committees: Transparency, Reputation, and Voting Rules," American Economic Review, American Economic Association, vol. 97(1), pages 150-168, March.
    4. Ederer, Florian & Stremitzer, Alexander, 2017. "Promises and expectations," Games and Economic Behavior, Elsevier, vol. 106(C), pages 161-178.
    5. Ellingsen, Tore & Johannesson, Magnus & Tjøtta, Sigve & Torsvik, Gaute, 2010. "Testing guilt aversion," Games and Economic Behavior, Elsevier, vol. 68(1), pages 95-107, January.
    6. Koch, Alexander K. & Morgenstern, Albrecht & Raab, Philippe, 2009. "Career concerns incentives: An experimental test," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 571-588, October.
    7. Michael P. Keane & David E. Runkle, 1998. "Are Financial Analysts' Forecasts of Corporate Profits Rational?," Journal of Political Economy, University of Chicago Press, vol. 106(4), pages 768-805, August.
    8. Dorothea Kübler & Georg Weizsäcker, 2003. "Information Cascades in the Labor Market," Journal of Economics, Springer, vol. 80(3), pages 211-229, November.
    9. Tanjim Hossain & Ryo Okui, 2013. "The Binarized Scoring Rule," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(3), pages 984-1001.
    10. Ananish Chaudhuri & Andrew Schotter & Barry Sopher, 2009. "Talking Ourselves to Efficiency: Coordination in Inter‐Generational Minimum Effort Games with Private, Almost Common and Common Knowledge of Advice," Economic Journal, Royal Economic Society, vol. 119(534), pages 91-122, January.
    11. Angela A. Hung & Charles R. Plott, 2001. "Information Cascades: Replication and an Extension to Majority Rule and Conformity-Rewarding Institutions," American Economic Review, American Economic Association, vol. 91(5), pages 1508-1520, December.
    12. Sebastian Fehrler & Niall Hughes, 2018. "How Transparency Kills Information Aggregation: Theory and Experiment," American Economic Journal: Microeconomics, American Economic Association, vol. 10(1), pages 181-209, February.
    13. Matthew Gentzkow & Jesse M. Shapiro, 2006. "Media Bias and Reputation," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 280-316, April.
    14. Lamont, Owen A., 2002. "Macroeconomic forecasts and microeconomic forecasters," Journal of Economic Behavior & Organization, Elsevier, vol. 48(3), pages 265-280, July.
    15. EllenE. Meade & David Stasavage, 2008. "Publicity of Debate and the Incentive to Dissent: Evidence from the US Federal Reserve," Economic Journal, Royal Economic Society, vol. 118(528), pages 695-717, April.
    16. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    17. Trueman, Brett, 1994. "Analyst Forecasts and Herding Behavior," The Review of Financial Studies, Society for Financial Studies, vol. 7(1), pages 97-124.
    18. Andrea Mattozzi & Marcos Y. Nakaguma, 2016. "Public versus Secret Voting in Committees," Working Papers, Department of Economics 2016_29, University of São Paulo (FEA-USP).
    19. Bogaçhan Çelen & Shachar Kariv, 2004. "Distinguishing Informational Cascades from Herd Behavior in the Laboratory," American Economic Review, American Economic Association, vol. 94(3), pages 484-498, June.
    20. Ottaviani, Marco & Sorensen, Peter, 2001. "Information aggregation in debate: who should speak first?," Journal of Public Economics, Elsevier, vol. 81(3), pages 393-421, September.
    21. Khalmetski, Kiryl, 2016. "Testing guilt aversion with an exogenous shift in beliefs," Games and Economic Behavior, Elsevier, vol. 97(C), pages 110-119.
    22. Andrew Schotter, 2005. "Decision Making with Naïve Advice," Springer Books, in: Amnon Rapoport & Rami Zwick (ed.), Experimental Business Research, chapter 0, pages 223-248, Springer.
    23. Schotter, Andrew & Sopher, Barry, 2007. "Advice and behavior in intergenerational ultimatum games: An experimental approach," Games and Economic Behavior, Elsevier, vol. 58(2), pages 365-393, February.
    24. Harrison, Glenn W. & Martínez-Correa, Jimmy & Swarthout, J. Todd, 2013. "Inducing risk neutral preferences with binary lotteries: A reconsideration," Journal of Economic Behavior & Organization, Elsevier, vol. 94(C), pages 145-159.
    25. Dufwenberg, Martin & Gneezy, Uri, 2000. "Measuring Beliefs in an Experimental Lost Wallet Game," Games and Economic Behavior, Elsevier, vol. 30(2), pages 163-182, February.
    26. Tilman Ehrbeck & Robert Waldmann, 1996. "Why Are Professional Forecasters Biased? Agency versus Behavioral Explanations," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 111(1), pages 21-40.
    27. John R. Graham, 1999. "Herding among Investment Newsletters: Theory and Evidence," Journal of Finance, American Finance Association, vol. 54(1), pages 237-268, February.
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    Cited by:

    1. Dirk Bergemann & Marco Ottaviani, 2021. "Information Markets and Nonmarkets," Cowles Foundation Discussion Papers 2296, Cowles Foundation for Research in Economics, Yale University.
    2. David Danz & Lise Vesterlund & Alistair J. Wilson, 2020. "Belief Elicitation: Limiting Truth Telling with Information on Incentives," NBER Working Papers 27327, National Bureau of Economic Research, Inc.
    3. Yuan Liu & Hongmin Chen, 2022. "Cheap‐talk advertising, product experience, and reputation concern," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(7), pages 3165-3175, October.

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    More about this item


    Forecasting; Experts; Reputation; Cheap talk; Laboratory experiments;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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